Questions tagged [gpt]

For questions related to GPT (which stands for Generative Pre-Training), which is a combination of transformers (proposed in "Attention is All You Need") and unsupervised pre-training for solving language tasks, such as machine translation. GPT was proposed in "Improving Language Understanding by Generative Pre-Training" (2018) by Open AI. There's also GPT-2, which was proposed in "Language Models are Unsupervised Multitask Learners" (2019) by Open AI.

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1answer
53 views

Is GPT-3 an early example of Strong AI in a Narrow setting?

In GPT-2, the large achievement was being able to generate coherent text over a long-form while maintaining context. This was very impressive but for GPT-2 to do new language tasks, it had to be ...
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0answers
48 views

What is the efficiency of trained neural networks?

Training neural networks takes a while. My question is, how efficient is a neural network that is completely trained (assuming it's not a model that is constantly learning)? I understand that this is ...
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36 views

Can in principle GPT language models learn physics?

Does anyone know of research involving the GPT models to learn not only regular texts, but also learn from physics books with the equations written in latex format? My intuition is that the model ...
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2answers
300 views

How much computing power does it cost to run GPT-3? [closed]

I know it cost around $4.3 million dollars to train, but how much computing power does it cost to run the finished program? IBM Watson chatbot AI only costs a few cents per chat message to use, ...
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0answers
60 views

How large should the corpus be to optimally retrain the GPT-2 model?

I just started working with the GPT-2 models and want to retrain one on a pretty narrow topic, so I have problems finding training material. How large should the corpus be to optimally retrain the GPT-...
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1answer
340 views

What exactly are the “parameters” in GPT-3's 175 billion parameters and how are they chosen/generated?

When I studied neural networks, parameters were learning rate, batch size etc. But even GPT3's ArXiv paper does not mention anything about what exactly the parameters are, but gives a small hint that ...
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1answer
165 views

Why is GPT-3 such a game changer?

I've been hearing a lot about GPT-3 by OpenAI, and that it's a simple to use API with text in text out and has a big neural network off 175B parameters. But how did they achieve this huge number of ...
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1answer
64 views

Is the size of a neural network directly linked with an increase in its inteligence?

Just came across this article on GPT-3, and that lead me to the question: In order to make a certain kind of neural network architecture smarter all one needs to do is to make it bigger? Also, if that ...
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42 views

What are the training and optimization technique to train GPT-2 with 1.5B parameters?

I am able to train 345M parameter GPT-2 using DialoGPT on Reddit data topics like AskReddit, Askmen, AskWomen, casualConvo, etc. And I using AWS p3dn.24xlarge instance with 256GB GPU. It is trained ...
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0answers
142 views

GPT-2: (Hardware) requirements for fine-tuning the 774M model

I wonder if there's anyone who has actually succeeded in fine-tuning GPT-2's 774M model without using cloud TPU's. My GeForce RTX 2070 SUPER couldn't handle it in previous attempts. I'm running ...
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0answers
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How can I use GPT-2 to modify seed text of one form into a different form (LENGTH INVARIANT) whilst retaining meaning?

I am currently starting a research project whereby I am trying to convert text of one form into another. i.e. If I were to write a seed sentance of the form "Scientists have finally achieved the ...
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38 views

Pretrained Models for Keyword-Based Text Generation

I'm looking for an implementation that allows me to generate text based on a pre-trained model (e.g. GPT-2). An example would be gpt-2-keyword-generation (click here for demo). As the author notes, ...
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58 views

Can we use GPT-2 to smooth out / correct text?

Are we able to use models like GPT-2 to smooth out/correct text? For instance if I have two paragraphs that need some text to make the transition easier to read, could this text be generated? And, ...
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1answer
170 views

Is the Mask Needed for Masked Self-Attention During Inference with GPT-2

My understanding is that masked self-attention is necessary during training of GPT-2, as otherwise it would be able to directly see the correct next output at each iteration. My question is whether ...
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0answers
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Training with many CPU cores doesn't improve performance

I ran my job on a computing cluster: first with 4 cores, then with 32 cores (2 nodes). But the training time is pretty much exactly the same for both of them: ~67 seconds per step. I am trying to ...
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0answers
86 views

How to use TPU for real-time low-latency inference?

I use Google's Cloud TPU hardware extensively using Tensorflow for training models and inference, however, when I run inference I do it in large batches. The TPU takes about 3 minutes to warm up ...
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1answer
236 views

Is it possible to use the GPT-2 model for time-series data prediction?

Is it possible and how trivial (or not) might it be (if possible) to retrain GPT-2 on time-series data instead of text?
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0answers
68 views

How to interpret a large variance of the loss function?

How do I interpret a large variance of a loss function? I am currently training a transformer network (using the software, but not the model from GPT-2) from scratch and my loss function looks like ...
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0answers
41 views

How can I generate a document from a single word using GPT or BERT?

I have a dataset of 100000 documents each labelled with a topic to it. I want to create a model such that, given a topic, the model can generate a document from it. I came across language models GPT,...
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1answer
456 views

How do we know if GPT-2 is a better language model?

You may have heard of GPT2, a new language model. It has recently attracted attention from the general public as the foundation that published the paper, OpenAI, ironically refused to share the whole ...
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2answers
961 views

Where can I find pre-trained language models in English and German?

Where can I find (more) pre-trained language models? I am especially interested in neural network-based models for English and German. I am aware only of Language Model on One Billion Word Benchmark ...